Improving subpixel classification by incorporating prior information in linear mixture models

IEEE Transactions on Geoscience and Remote Sensing

Volumn 49, Issue 3, 2011, Pages 1001-1013

  Kasetkasem, Teerasit ^a   Arora, Manoj K ^b   Varshney, Pramod K ^c   Areekul, Vutipong ^a  

^a KASETSART UNIVERSITY   (Thailand)

^b INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

^c Syracuse University   (United States)

Author keywords

Image classification; Linear mixture model (LMM); Maximum a posteriori (MAP) criteria; Remote sensing; Subpixel classification

Indexed keywords

ERROR COST FUNCTION; LAND COVER; LINEAR MIXTURE MODEL (LMM); LINEAR MIXTURE MODELS; MAXIMUM A POSTERIORI; MAXIMUM A POSTERIORI (MAP) CRITERIA; NUMERICAL RESULTS; OCCURRENCE PROBABILITY; OPTIMIZATION PROBLEMS; PRIOR INFORMATION; SUB-PIXEL CLASSIFICATION;

ALGORITHMS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; MIXTURES; OPTIMIZATION; RADAR TARGET RECOGNITION; REMOTE SENSING;

COST FUNCTIONS;

ALGORITHM; IMAGE CLASSIFICATION; LAND COVER; PIXEL; REMOTE SENSING;

EID: 79952039654     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2072785     Document Type: Article

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